Conceptual FOG Based Architecture for Monitoring and Acceleration of Bone Fracture
S. Jyothi1, Raju Anitha2, CSR Prabhu3

1S. Jyothi, Research Scholar, Department of Computer Science, KLU, Guntur (Andhra Pradesh), India.
2Dr. Raju Anitha, Associate Professor, Department of Computer Science, KLU, Guntur (Andhra Pradesh), India.
3Dr. CSR Prabhu, Director Research, KMIT, Hyderabad (Telangana), India.
Manuscript received on 06 June 2019 | Revised Manuscript received on 30 June 2019 | Manuscript Published on 04 July 2019 | PP: 779-784 | Volume-8 Issue-1S4 June 2019 | Retrieval Number: A11430681S419/2019©BEIESP
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Abstract: In the backdrop of an emerging scenario marked by a predominantly older populace, burgeoning costs of living amidst depleting resources, Cloud computing and IoT offer a ray of hope, particularly while developing e-Health system, with patient at the core of the healthcare pyramid. Telemedicine is a novel application that offers healthcare services such as diagnosis, consultation as well as treatment that reaches the most efficient levels with introduction of smart healthcare solutions. Nonetheless, IoT-driven healthcare requires to conquer multiple hurdles like complexities in data storage on cloud servers, security and privacy aspects, prohibitively high expenses incurred on perpetual data accumulation, other than energy-efficiency challenges and maintenance of sensors based out of cloud servers. In this paper, the primary focus is on devising a novel construct around the concept, Fog computing, particularly from the point of view of Tele medical IoT. As is commonly understood, Fog computing as a prototype allows cloud computing services to reach the periphery of a network. In a manner identical to cloud, Fog enables end users to receive data, computation, storage, and application services. As a case study, in this paper, an attempt has been made to develop a service-oriented architecture that monitors and accelerates healing in cases of bone fracture applying fog computing. In fact, , this architecture applies a sensing module on an energy-efficient embedded computer to perform data mining and data analytics operation on raw data that is sourced from sensing modules utilized in such telehealth operations. This embedded computer system assembles such sensed data in a time series before analyzing and discovering the identical patterns, which later stores, extracts novel patterns as well as transmits clinically-suitable data via network to the cloud based in a hospital.
Keywords: Cloud Computing, Fog Computing, IoT, Telemedicine.
Scope of the Article: Network Architectures